Meeting Title: [Eden] Daily Standup Date: 2025-07-31 Meeting participants: Fireflies.ai Notetaker Tigran, Amber Lin, Vashdev Heerani, Andrew O’Neil, Annie Yu, Awaish Kumar, Robert Tseng


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1 00:00:43.440 00:00:44.879 Amber Lin: Hi! Mastav.

2 00:00:48.100 00:00:48.860 Vashdev Heerani: Hello!

3 00:00:49.280 00:00:54.150 Amber Lin: Hi! Have you been able to start with? Have you been assigned any tasks.

4 00:00:55.430 00:01:02.160 Vashdev Heerani: Yes, I am assigned to to find the event, count.

5 00:01:03.870 00:01:04.989 Vashdev Heerani: Are they done.

6 00:01:05.560 00:01:05.900 Amber Lin: Sure.

7 00:01:05.900 00:01:06.979 Vashdev Heerani: From, yeah.

8 00:01:07.200 00:01:11.586 Amber Lin: I see. Do you have enough context from that? Does? Did a wish

9 00:01:11.900 00:01:16.770 Vashdev Heerani: Yeah, yes, I I had that discussion yesterday with Avesh regarding this.

10 00:01:16.770 00:01:19.309 Amber Lin: Okay, yeah, that sounds good.

11 00:01:22.280 00:01:26.349 Amber Lin: Sorry. Can you look at? Can you tell me what number of ticket that is.

12 00:01:29.260 00:01:30.650 Vashdev Heerani: Yeah, give me a second.

13 00:01:34.480 00:01:37.409 Vashdev Heerani: So it’s a 4, 2, 4.

14 00:01:38.730 00:01:43.450 Amber Lin: Okay, I’ll I’ll remember that. Hi, Andrew.

15 00:01:43.650 00:01:44.760 Andrew O’Neil: Hello!

16 00:01:44.760 00:01:59.840 Amber Lin: Hi, I just wanted to, because I saw Robert and yours messages yesterday. I just wanna use a bit of time right now to confirm. If these are valid tickets to add, and then I think you can feel free to hop off.

17 00:02:00.600 00:02:10.969 Andrew O’Neil: Okay, perfect, perfect. Yeah. It seems like there’s a lot of tickets that are. I don’t know if they’re duplicates is the right word. But certainly.

18 00:02:10.979 00:02:14.249 Amber Lin: Don’t have the full context of what they mean.

19 00:02:15.140 00:02:36.340 Andrew O’Neil: Yeah, yeah, yeah, well, and and what’s hard is, there are. We’re kind of receiving different messages from the team as to like how they want us to proceed. So it’s like one ticket, I think, was created to like, you know, for a work stream that we’re kind of pivoting away from that’s kind of that’s kind of adding to the complexity.

20 00:02:36.340 00:02:36.680 Amber Lin: Okay.

21 00:02:37.930 00:02:42.590 Andrew O’Neil: But yeah, we we can start, you know. I don’t know if we want to go through each one, but I can definitely.

22 00:02:42.590 00:02:53.749 Amber Lin: Let’s let’s do that so totally. Do you want me to share screen? Do you want to share screen? I organize it in the different milestones.

23 00:02:54.120 00:03:01.329 Andrew O’Neil: Okay, yeah, yeah, we can start from the top. Then if that works, let’s see. Yes. So.

24 00:03:02.590 00:03:06.750 Amber Lin: Robert created perfect, valid.

25 00:03:06.750 00:03:07.830 Andrew O’Neil: That is, yep.

26 00:03:08.030 00:03:16.900 Amber Lin: I changed this one into a final Qa, just because of all of the other ones I created. This was the audit ticket before.

27 00:03:17.390 00:03:18.439 Andrew O’Neil: Got it. Got it.

28 00:03:19.380 00:03:22.610 Amber Lin: And then, based on that, we’ll have

29 00:03:25.250 00:03:31.740 Amber Lin: So we have Block repeat, purchase events for firing, and Pixel.

30 00:03:34.198 00:03:38.180 Amber Lin: We have disabled view through attribution and Meta ad settings

31 00:03:40.060 00:03:44.680 Amber Lin: are they? Are these so like valid tickets?

32 00:03:45.020 00:03:48.738 Andrew O’Neil: Let’s see. So yeah, block repeat purchases.

33 00:03:49.710 00:03:56.900 Andrew O’Neil: yeah. So that one repeat purchase events. Wait. Yeah. Can you click into that ticket? 5, 76.

34 00:03:57.040 00:03:58.340 Andrew O’Neil: Let’s see.

35 00:03:58.990 00:04:19.350 Andrew O’Neil: for new intakes. Yes, the only so. Yes, this ticket is valid, but I have to. This is this is one of the the requirements that the team, the Eden team is kind of they’re not sure of. To be honest with you, like one person told us it should fire for every purchase. Another person said, Oh.

36 00:04:19.350 00:04:20.579 Amber Lin: Yeah, that’s what I was confused

37 00:04:21.459 00:04:25.009 Amber Lin: 2 messages about different things, and I had to change it, too.

38 00:04:25.010 00:04:45.299 Andrew O’Neil: Yeah. Yeah. So I I need to sync with Robert on, like what the and it’s hard to amber. I don’t know if you know, like who the ultimate decision maker is on their side, but it seems like they have different members of their team that are articulating different things to us.

39 00:04:46.540 00:04:53.529 Amber Lin: yeah, I see that too. Robert will be a be able to give you who to listen to I just put it as blocked just in case.

40 00:04:53.530 00:04:55.049 Andrew O’Neil: Perfect. Okay. Great.

41 00:04:55.350 00:05:01.570 Amber Lin: Okay. Quickly. Now and then disable view through attribution. Meta add settings.

42 00:05:01.850 00:05:24.830 Andrew O’Neil: Yes, yeah, that one I can. I can help with. Yeah, let me just make sure that I have the right permissions there, because I know I have permissions to go and look at their events, but the campaigns are often their own setting. Let me check that. I have the right permissions there to do that.

43 00:05:25.080 00:05:25.580 Amber Lin: Okay.

44 00:05:26.250 00:05:29.300 Andrew O’Neil: That I could do that right now, because it’s not

45 00:05:29.410 00:05:32.876 Andrew O’Neil: not too difficult to see.

46 00:05:34.190 00:05:41.640 Andrew O’Neil: let me go to a Facebook campaign manager.

47 00:05:42.090 00:05:43.110 Andrew O’Neil: Let’s see.

48 00:05:45.210 00:05:47.500 Andrew O’Neil: Sign in.

49 00:05:50.340 00:05:52.360 Andrew O’Neil: Okay, let’s see.

50 00:05:53.810 00:05:55.680 Andrew O’Neil: Okay. Eden

51 00:05:56.140 00:06:02.725 Andrew O’Neil: Health Club. Okay. Yeah. No. I. I do have the right permission. So yes, that one I can. I can action on that one.

52 00:06:03.480 00:06:09.170 Amber Lin: Okay, sounds good, and then let’s go back here.

53 00:06:10.350 00:06:14.870 Amber Lin: Remove 1st time purchase. I guess that’s 1’s the that one.

54 00:06:14.870 00:06:15.459 Andrew O’Neil: Oh, yeah.

55 00:06:15.460 00:06:16.570 Amber Lin: Clear, one.

56 00:06:16.580 00:06:22.200 Andrew O’Neil: Yeah, that one. That one’s the yeah. Also kind of related to yep. Yep.

57 00:06:22.200 00:06:28.299 Amber Lin: Duplicate tickets, feel free to delete merge, do anything with them. I just wanted you to have something to start with.

58 00:06:28.890 00:06:30.640 Andrew O’Neil: Perfect. Yeah, yeah, absolutely.

59 00:06:30.640 00:06:37.910 Amber Lin: Okay? So I’m putting that as blocked as well. So audit non-purchase pixel copy events.

60 00:06:38.610 00:06:47.360 Andrew O’Neil: Yup, yeah, this one is pretty straightforward. Yeah, I can. I can, definitely this is one, yeah, that that I can. I can definitely help with.

61 00:06:47.360 00:06:52.749 Amber Lin: Sounds good. We’re just seeing that one. And then this is the this is the other one

62 00:06:53.620 00:06:59.920 Amber Lin: that shared event. Yes, yes, this is one I’ll probably need Robert’s help with to.

63 00:07:00.488 00:07:06.911 Andrew O’Neil: Cause he’ll be cause right now. The our data engineer is is outright. That’s Henry.

64 00:07:08.963 00:07:09.469 Andrew O’Neil: But but.

65 00:07:09.470 00:07:14.119 Amber Lin: Henry is on a data engineer. If you need data engineering help which can help you with that.

66 00:07:14.120 00:07:21.739 Andrew O’Neil: Oh, wish. Okay, okay, perfect. But yes, we’ll need some data engineering help for this one to like.

67 00:07:21.890 00:07:32.250 Andrew O’Neil: essentially, add the event. Id to the payload. That’s gonna need to come from the the data pipeline itself. We’re gonna need to modify that.

68 00:07:32.250 00:07:39.339 Amber Lin: Okay? What’s the sequence? And what’s the due date you will need this by? Is this blocking anything else?

69 00:07:39.510 00:07:40.680 Andrew O’Neil: Let’s see.

70 00:07:41.875 00:07:43.480 Andrew O’Neil: So this one.

71 00:07:43.480 00:07:44.350 Awaish Kumar: Is this?

72 00:07:44.874 00:07:48.919 Awaish Kumar: Is this more like data engineering work or Cdp work.

73 00:07:49.838 00:07:52.679 Amber Lin: Work is owned by Henry.

74 00:07:53.660 00:07:59.710 Andrew O’Neil: I would say, this is more data engineering work. Yeah.

75 00:07:59.710 00:08:05.659 Awaish Kumar: Like. So if it is about like setting up the tables

76 00:08:06.313 00:08:10.660 Awaish Kumar: for sending these get like collecting these event. Ids.

77 00:08:11.270 00:08:19.629 Awaish Kumar: that’s on your engineering. But if it’s about like pushing that to Meta through segment, it’s more like Henry.

78 00:08:20.250 00:08:29.989 Andrew O’Neil: Got it. Yeah, yeah. So it doesn’t exist in segment right now. So yeah, so it’s more of a data engineering thing at this point to get it into those those tables.

79 00:08:32.076 00:08:33.210 Awaish Kumar: Okay. Okay.

80 00:08:34.039 00:08:43.029 Amber Lin: Yeah. When would you? I know a ways is doing this ticket, and we want it by the end of week. So turning a segment into DVD models. When would you need this? By.

81 00:08:43.580 00:08:55.079 Andrew O’Neil: Yeah, so this 5, 77 will help us to set up like, it’s a dependency for purchase tracking in 4, Meta

82 00:08:55.320 00:09:22.680 Andrew O’Neil: as well. Essentially, we’re having like this event. Id. We need it to, or we need to add it to segment, so that we can tell Meta that the say that our purchase that’s coming from segment in the purchase, that they might see from the pixel are the same one. So it doesn’t double count things. So, yeah, this is kind of related to the Meta purchase tracking work stream.

83 00:09:23.720 00:09:28.429 Amber Lin: Okay, so that will be so when.

84 00:09:28.430 00:09:30.259 Awaish Kumar: Can we ask about the.

85 00:09:30.690 00:09:32.509 Awaish Kumar: 5, 5, 7, like.

86 00:09:32.760 00:09:34.109 Amber Lin: 5, 5, 7.

87 00:09:34.110 00:09:37.140 Awaish Kumar: Yeah, can. I can watch them like, take it.

88 00:09:39.510 00:09:40.880 Amber Lin: That’s your call.

89 00:09:42.330 00:09:45.960 Awaish Kumar: Like I. I wanted to ask questions.

90 00:09:46.740 00:09:47.430 Amber Lin: Oh, okay.

91 00:09:55.080 00:10:01.669 Vashdev Heerani: Okay. So I, I can take this. I need more context related to this, I can take.

92 00:10:01.670 00:10:07.459 Awaish Kumar: Yeah, like, this is something we need by end of week. That means by tomorrow.

93 00:10:10.079 00:10:18.470 Awaish Kumar: So like, we already have a Dbt model. The context is that we want to connect segment with Dbt

94 00:10:18.780 00:10:21.740 Awaish Kumar: project and

95 00:10:22.220 00:10:29.620 Awaish Kumar: and see if if it, if segment directly, can run our Dbt model instead of directly providing a query.

96 00:10:29.970 00:10:35.270 Awaish Kumar: So I can share more in a separate call. But okay, that’s sure.

97 00:10:35.270 00:10:35.930 Awaish Kumar: It’s.

98 00:10:36.150 00:10:37.340 Amber Lin: Sounds good.

99 00:10:37.340 00:10:55.350 Amber Lin: I just wanna be conscious of Andrew’s time. Andrew, can you give me roughly due dates for these tickets? You can say, maybe end of this week, or maybe end of next week, or maybe something between. But just just so that I have a rough idea what gets completed 1st before the other ones.

100 00:10:55.350 00:11:23.381 Andrew O’Neil: Yeah, and that’s that’s kind of where you know. Maybe this is where I should sync with Robert. It’s unclear. To me. The it seems like Meta is the priority. So that so I would say, if if the the data engineering team can complete 5 77 by, you know, this week or early next week. Then I would say comfortably, end of next week would be a good

101 00:11:23.760 00:11:24.210 Amber Lin: Okay.

102 00:11:24.210 00:11:31.100 Andrew O’Neil: Deadline for the the work to get the the purchase tracking straightened up.

103 00:11:31.510 00:11:33.399 Amber Lin: Okay, yeah, sounds good.

104 00:11:34.246 00:11:42.360 Amber Lin: So I’m gonna say, it’s roughly end of cycle.

105 00:11:42.800 00:11:45.740 Amber Lin: Okay.

106 00:11:46.360 00:11:52.989 Amber Lin: okay, yeah, that sounds good. So I’ll I’ll ask the team what they, when they think 5 77 can get done.

107 00:11:53.300 00:11:53.980 Andrew O’Neil: Cool.

108 00:11:56.730 00:12:04.939 Amber Lin: All right. Yeah, I think that’s all for this project. We’ll groom these later. I don’t think we need them yet, but I think. Thank you for joining. Stand up.

109 00:12:05.170 00:12:07.410 Andrew O’Neil: Yeah, absolutely. Yeah. Great to chat.

110 00:12:07.800 00:12:08.560 Andrew O’Neil: Alright, thanks everyone.

111 00:12:14.460 00:12:21.590 Amber Lin: Okay, so us, they’re his tickets.

112 00:12:21.720 00:12:23.689 Amber Lin: Think right? Here.

113 00:12:27.620 00:12:28.780 Amber Lin: I think.

114 00:12:29.690 00:12:37.030 Amber Lin: So. These are data engineering tickets.

115 00:12:39.150 00:12:43.000 Amber Lin: This, you’ll sync and get it on track for end of this week.

116 00:12:43.100 00:12:49.009 Amber Lin: Do we know if do you know when this will get done by

117 00:12:56.190 00:12:57.380 Amber Lin: higher wish.

118 00:12:57.560 00:13:04.920 Awaish Kumar: Yeah, like, it’s, it’s about putting event. Id in one of the

119 00:13:05.130 00:13:09.260 Awaish Kumar: meta model we created like Robert created. Basically.

120 00:13:09.780 00:13:15.000 Awaish Kumar: yeah, if that is, I can can. The like can finish it today.

121 00:13:15.610 00:13:21.830 Amber Lin: Okay, yeah, I know. Robert put it as urgent. I’ll say today, do you know how many points that is?

122 00:13:23.180 00:13:25.380 Awaish Kumar: Yeah. It’s just put one.

123 00:13:25.570 00:13:26.363 Amber Lin: Oh, okay.

124 00:13:27.650 00:13:31.120 Amber Lin: One question, all right.

125 00:13:35.140 00:13:36.130 Amber Lin: Okay.

126 00:13:39.950 00:13:43.699 Amber Lin: Oh, Robert is here. Robert, are we doing?

127 00:13:44.220 00:13:46.919 Amber Lin: Are we doing? Still doing the farm? Ops?

128 00:13:48.040 00:13:49.310 Amber Lin: Forecasting.

129 00:13:53.290 00:13:57.732 Robert Tseng: I don’t. I’m I don’t know.

130 00:13:59.305 00:14:02.859 Amber Lin: And should focus.

131 00:14:05.270 00:14:07.109 Robert Tseng: Yeah, I mean, I think the.

132 00:14:07.110 00:14:08.350 Amber Lin: Project, calls.

133 00:14:08.580 00:14:15.669 Robert Tseng: Anything like, yeah, the the tagging and tracking work is what I care about. We’re behind on that. So I’m pushing this out.

134 00:14:15.870 00:14:21.269 Amber Lin: Okay? So I will move it to a different cycle.

135 00:14:22.920 00:14:23.760 Amber Lin: Okay, there we go.

136 00:14:23.760 00:14:34.839 Robert Tseng: I mean. Rebecca may ask for it, and I may have to do it later, but like I don’t know, like I just. There’s I don’t know why I have to be involved in doing every, every task. It just like

137 00:14:35.290 00:14:36.510 Robert Tseng: it, just.

138 00:14:36.510 00:14:43.030 Amber Lin: Have you tag me, and then and then I’ll ask her for the deadline again and tell her about other stuff we’re doing. How’s that.

139 00:14:43.600 00:15:09.360 Robert Tseng: Yeah, but she wants it before the end of the month is end of the month. So I mean, I’m gonna I’m gonna have to do it like I don’t know. Like I I’ve blocked off like my afternoon to just do eat and stuff like I don’t know what to do. There’s just so many tickets. And I feel like we’re behind. So I’m just, I don’t want to move anything out. I’m just gonna if I sit down and just spend an hour or 2 HI think I will do like I’ll get a lot done. So.

140 00:15:09.360 00:15:25.579 Amber Lin: I I get you. I felt like that yesterday until it sat down. Andrew, said. He, will sync with you about these in a bit. I don’t know if you’ve heard our conversation, but he has some questions about conflicting requests from Eden people, so he will sync with you, and I asked him to update tickets.

141 00:15:25.580 00:15:26.700 Robert Tseng: No. Okay.

142 00:15:30.650 00:15:39.680 Amber Lin: mostly these is, is it okay? Is it 1st time purchase only, or multiple? I think these are the only 2 that was confusing.

143 00:15:44.920 00:15:47.709 Robert Tseng: yeah, these are outdated, based off of the.

144 00:15:48.130 00:15:55.630 Amber Lin: Yeah, I had. I saw your message in our channel, and I saw any other channel, and they talked about opposite things. So I was really confused.

145 00:15:56.450 00:16:03.350 Robert Tseng: Yeah, I mean, this is when they came on the call yesterday and just yelled for like 30 min. So I think like.

146 00:16:05.740 00:16:13.449 Robert Tseng: no, we’re not removing the 1st time. Purchase filter. We’re keeping that we’re removing

147 00:16:14.713 00:16:19.440 Robert Tseng: like the sent to pharmacy like filter. So

148 00:16:20.150 00:16:23.140 Robert Tseng: I I thought I like. I thought I explained this like in the.

149 00:16:23.140 00:16:23.690 Amber Lin: Oh!

150 00:16:23.690 00:16:28.329 Robert Tseng: In the marketing analytics Channel, I said, this is what we’re doing, so I don’t know.

151 00:16:28.330 00:16:29.010 Amber Lin: I see.

152 00:16:29.780 00:16:30.770 Robert Tseng: I guess.

153 00:16:30.770 00:16:31.230 Robert Tseng: Just have.

154 00:16:31.970 00:16:44.680 Amber Lin: Well, I made the tickets with limited understanding, and didn’t ask Andrew because it was really late last night. Just asked him earlier this morning, but he didn’t. He didn’t say any objections. Tell me the name again.

155 00:16:48.590 00:16:49.810 Amber Lin: Sent to pharmacy.

156 00:16:52.470 00:16:53.430 Amber Lin: Okay?

157 00:16:53.430 00:17:20.740 Robert Tseng: It. It’s not for him. He he is this like, I mean, I I feel like either a way. Sure, I have to do it. Yeah, cause Andrew doesn’t actually touch anything in our data warehouse. All he all he’s doing is queuing events. And I mean, he’s he’s supposed to be on any of the calls with the stakeholders, but he wasn’t there yesterday, because it was like a spontaneous call. So he’s out of the loop like I just.

158 00:17:21.020 00:17:23.089 Robert Tseng: It’s just kind of

159 00:17:23.240 00:17:30.400 Robert Tseng: like I feel like I have to have 4 calls just to have the same thing like I might as well, just I don’t know like I it’s like.

160 00:17:30.400 00:17:33.299 Amber Lin: I know you feel like you might as well just do it yourself.

161 00:17:33.420 00:17:34.670 Robert Tseng: Yeah, like.

162 00:17:34.670 00:17:35.430 Amber Lin: Oh!

163 00:17:35.680 00:17:36.390 Amber Lin: If.

164 00:17:36.390 00:17:47.729 Robert Tseng: Andrew’s out of the loop like he’s he’s 1 day he he was inactive for one day and then. Now he doesn’t. He’s not on the latest requirements, because he wasn’t there on, like the other 2 calls I took yesterday so.

165 00:17:47.730 00:17:48.220 Amber Lin: Hmm.

166 00:17:48.220 00:17:57.909 Robert Tseng: Now I have to call him, and then tell him what’s the latest, and then he’s not doing the work. It’s still gonna be a wish, and then I have to go call a wish like it, just like doesn’t make sense like I.

167 00:17:57.910 00:17:58.480 Amber Lin: Well.

168 00:17:58.480 00:18:13.459 Robert Tseng: I I don’t even wanna update these tickets like to me in my mind, I’m coming out of this meeting, and I’m just gonna change the model myself, and I’m gonna do the forecasting myself like I’m i i think that’ll just that’s faster than me call scheduling all these calls.

169 00:18:14.750 00:18:21.989 Amber Lin: Okay, if that’s the case, let’s do that. And then I really really want to talk about this in the retro. It seems like, this is

170 00:18:22.180 00:18:24.000 Amber Lin: this is burning you off.

171 00:18:24.590 00:18:31.950 Robert Tseng: Yeah, I mean, it’s just I. I didn’t actually hand off anything. I I don’t know. We’ll just well, we can save it for Friday, like, yeah.

172 00:18:31.950 00:18:34.830 Amber Lin: Yeah, let’s talk. Let’s talk about it. I think this is important.

173 00:18:34.830 00:18:35.380 Robert Tseng: Yeah.

174 00:18:35.640 00:18:36.340 Amber Lin: Okay.

175 00:18:43.040 00:18:43.900 Amber Lin: Okay.

176 00:18:49.280 00:18:50.760 Amber Lin: Frequency.

177 00:18:51.906 00:18:56.219 Amber Lin: This one I signed to Vashav.

178 00:18:57.001 00:19:00.770 Amber Lin: Wish. Have you taken a look? Is this.

179 00:19:05.140 00:19:12.320 Amber Lin: I would say, this is not as high of a priority. But do you think this type of ticket is something rash? I can start to take.

180 00:19:16.730 00:19:21.359 Awaish Kumar: Yeah, like, he will need more of context here. But yeah, he can.

181 00:19:23.910 00:19:30.859 Amber Lin: I see, I would say, prioritize this.

182 00:19:31.200 00:19:34.950 Amber Lin: I’m sorry prioritize this before the other one,

183 00:19:45.190 00:19:46.160 Amber Lin: okay.

184 00:19:47.539 00:19:55.120 Amber Lin: emr, team we’re booking the meeting, and that me and wish have a meeting later to talk about the roadmap.

185 00:19:56.386 00:20:00.069 Amber Lin: Robert, there’s another task for you. Okay.

186 00:20:00.450 00:20:08.250 Robert Tseng: Yeah for Adam stuff I’m not like, I just can’t like, I don’t have. I don’t have time to talk about you more. I just wrote it. I don’t have time to figure this out like.

187 00:20:08.430 00:20:20.999 Robert Tseng: I don’t know you guys are spending time with the Emr team like I I’m just gonna put it on, Henry. Like, I I don’t know. Like to me, it’s just a communication thing. And just I don’t.

188 00:20:21.710 00:20:22.600 Robert Tseng: Yeah, like.

189 00:20:22.600 00:20:23.120 Amber Lin: Yeah, I got it.

190 00:20:23.250 00:20:23.870 Robert Tseng: Yeah.

191 00:20:25.776 00:20:28.009 Amber Lin: Wash recording.

192 00:20:29.250 00:20:31.899 Amber Lin: I forgot what day it is.

193 00:20:32.960 00:20:37.050 Amber Lin: Backgrounds that’s specific.

194 00:20:45.953 00:20:48.769 Amber Lin: On this one. Any.

195 00:20:49.000 00:20:55.909 Amber Lin: This is your tickets for Jonah. I know you said this was the same as one of the

196 00:21:00.870 00:21:01.830 Amber Lin: okay.

197 00:21:09.680 00:21:10.780 Amber Lin: Oh, okay.

198 00:21:11.210 00:21:16.770 Amber Lin: So we got all of the do. We have all of these.

199 00:21:17.570 00:21:20.960 Amber Lin: If we got a few weeks ago, can we reproduce it now?

200 00:21:21.200 00:21:32.629 Annie Yu: Yes, we provided them a monthly aggregation, but it looks like they here. They do want monthly aggregation and the order level. So that’s something.

201 00:21:33.290 00:21:39.820 Annie Yu: But but just be mindful that not all all the orders we got from Bask have dosage values.

202 00:21:40.500 00:21:44.590 Annie Yu: and that’s nothing we can really do about it.

203 00:21:45.542 00:21:50.170 Amber Lin: I see if we’re limited by data quality. Oh.

204 00:21:50.733 00:21:56.049 Amber Lin: once you get it, please flag it in the in the comments.

205 00:21:56.430 00:21:59.540 Amber Lin: And do you think you can get.

206 00:21:59.540 00:22:00.980 Annie Yu: Show you what I wrote here.

207 00:22:01.410 00:22:07.380 Amber Lin: Okay, yeah, yeah, that’s that’s good. That’s good. Can we get this to Jonah today?

208 00:22:07.380 00:22:07.930 Annie Yu: Yeah.

209 00:22:08.150 00:22:09.530 Amber Lin: Okay, awesome.

210 00:22:09.930 00:22:13.459 Amber Lin: And I’m asking Jonah about

211 00:22:14.578 00:22:21.839 Amber Lin: the this one. So I’m confirming what happens need to read his full message.

212 00:22:21.840 00:22:40.670 Robert Tseng: By by default. We’re never gonna have everything that they’re asking us for. We have to make assumptions. I think most of the things we can make assumptions for like anything that’s like a growth assumption. You, you can just estimate that anything that’s like missing historical data. Well, you can just use a 3 month rolling average like we have to be creative with how? We’re answering these questions

213 00:22:41.190 00:22:58.819 Robert Tseng: regarding vial size and products like, okay? Well, if we know the vial sizes and products for a single product. Well, we can assume that it’s probably something similar for the other products. And so as long as we’re like, it’s on the fly. Analysis is not accurate, but like it’s directional. So.

214 00:22:59.298 00:23:00.250 Amber Lin: Think, we yeah, yeah.

215 00:23:00.250 00:23:04.019 Robert Tseng: Can’t get stuck on stuff for weeks, and then like not make

216 00:23:04.580 00:23:06.790 Robert Tseng: not make assumptions like I just.

217 00:23:06.790 00:23:07.220 Amber Lin: Cool.

218 00:23:07.220 00:23:08.219 Robert Tseng: I don’t know what else to say.

219 00:23:08.220 00:23:12.090 Annie Yu: You have an assumption. That’s with the Cox

220 00:23:12.220 00:23:21.589 Annie Yu: work. So if I remember right said, with the cog work, Cox work, we can get to the point

221 00:23:22.000 00:23:28.887 Annie Yu: where we can say how much we should have been charged, and then compare that with the actual

222 00:23:31.190 00:23:34.900 Annie Yu: Whatever value.

223 00:23:34.900 00:23:55.250 Robert Tseng: Yeah, whatever we were actually charged. Yeah, I I think that’s that’s fine. Like, I’m like, I’m as I’m updating this forecast model. I don’t have everything that I asked him a lot, for. He’d been working on it for 6 weeks. I have no idea why we don’t have it, but I’m going to make a bunch of assumptions. And I’m gonna I’m gonna spit something out like it’s gonna it’s gonna come out. So it should be no excuse, we should be able to ship this stuff.

224 00:23:55.250 00:23:58.319 Annie Yu: Remember for this. 5, 7, 1. i did

225 00:23:58.680 00:24:06.466 Annie Yu: leave a comment, because I think this is this is what they’ve been working on.

226 00:24:07.800 00:24:08.240 Amber Lin: Oh!

227 00:24:08.240 00:24:10.800 Annie Yu: The image loading. But that image is

228 00:24:12.080 00:24:15.460 Annie Yu: essentially what information you wanted to get

229 00:24:17.340 00:24:25.590 Annie Yu: from Rebecca. So there’s a table that shows file size and I think the cost.

230 00:24:25.590 00:24:41.218 Amber Lin: Okay, I’ll note that because she wants it she will need to provide that information. We just don’t. If she didn’t, I don’t think she fully did, because we said, We’ll want to reduce scope to start from June 1st onwards.

231 00:24:45.760 00:24:48.340 Amber Lin: like this is a renegotiation.

232 00:24:48.520 00:25:11.560 Amber Lin: So I will get in Sync, I think. Step 3. I’ll get in sync with Rebecca about it. She needs to give us some of her details, and we’ll we’ll finalize our assumptions with her. And then let’s try and get Number one across. I’ll sync with Jonah to get their actual charge, which they should have.

233 00:25:12.159 00:25:18.940 Amber Lin: Since how else would they have realized that they got overcharged? So they will have their actual charge?

234 00:25:19.330 00:25:19.970 Amber Lin: Okay.

235 00:25:19.970 00:25:22.630 Annie Yu: So for the 5, 7, 1.

236 00:25:23.370 00:25:28.990 Annie Yu: I’m unclear if I should do anything now.

237 00:25:30.520 00:25:30.850 Annie Yu: Thank you.

238 00:25:30.850 00:25:31.190 Amber Lin: Nope.

239 00:25:31.190 00:25:39.749 Annie Yu: Reading at. I don’t I? I’m not clear what the requirements, because, in my view, it looks like this. It’s the same as that ticket.

240 00:25:40.102 00:25:53.140 Amber Lin: Yeah, I gotcha. I’ll go clarify. I think they want the 1st 1 first, st and then we’re gonna involve Rebecca, and she’s she can tell us what the requirements are, where she’s at, what she

241 00:25:53.490 00:26:00.229 Amber Lin: comfortable, making assumptions with what she really needs, data which she can provide. I’ll take note of that.

242 00:26:01.370 00:26:02.500 Annie Yu: Okay. Yeah.

243 00:26:02.500 00:26:03.779 Amber Lin: Do this 1 1.st

244 00:26:03.780 00:26:04.310 Annie Yu: Okay.

245 00:26:05.640 00:26:18.709 Amber Lin: Oh, Robert, I checked. I try to add. Each guest is, build a full seats, I would say. We don’t add them. Sorry. I know it’s contradicting, as what I said before.

246 00:26:19.180 00:26:21.860 Robert Tseng: Yeah, okay, that’s fine. I don’t really need them to look at it.

247 00:26:21.860 00:26:22.830 Amber Lin: Yeah. Okay.

248 00:26:31.820 00:26:33.180 Amber Lin: Oh.

249 00:26:37.420 00:26:38.200 Amber Lin: okay.

250 00:26:41.700 00:26:49.057 Amber Lin: So this one we push until Harry’s back.

251 00:26:51.710 00:26:57.960 Amber Lin: these are the main ad hoc tickets that came up.

252 00:26:59.300 00:27:19.799 Amber Lin: So Annie might need your help with this tableau ticket to update the naming conventions. They’ve provided everything in their school sheet, so you should be able to see it in the slack thread. Let me know if you don’t see it.

253 00:27:21.270 00:27:21.900 Annie Yu: Okay.

254 00:27:22.170 00:27:26.459 Amber Lin: Yeah, that’s 1. And then

255 00:27:29.670 00:27:30.350 Amber Lin: that’s it.

256 00:27:33.020 00:27:36.860 Amber Lin: Oh, a wish! Did you manage to check this.

257 00:27:45.060 00:27:48.249 Awaish Kumar: Sorry I was rude. I’m working on this one.

258 00:27:48.660 00:27:55.839 Awaish Kumar: and from the thread it looks like it’s more like investigation for the ad spend.

259 00:27:56.990 00:28:02.010 Awaish Kumar: But the description is talking about products, and I I don’t know what that is.

260 00:28:08.008 00:28:09.920 Amber Lin: What? What is unclear?

261 00:28:10.800 00:28:16.480 Awaish Kumar: So from the threads. I see that, like we are talking about ad spend for the med kits.

262 00:28:17.110 00:28:19.720 Awaish Kumar: And how it is distributed across different markets.

263 00:28:19.830 00:28:24.280 Awaish Kumar: and that does not seem to be correct, like as expected.

264 00:28:24.490 00:28:27.850 Awaish Kumar: And I’m working on to investigate that part.

265 00:28:28.050 00:28:34.100 Awaish Kumar: But the the these, like 3 lines on the top, like we are moving from

266 00:28:34.490 00:28:38.120 Awaish Kumar: new products to yeah, that one is.

267 00:28:38.120 00:28:45.909 Annie Yu: Should be. That’s something that we will do on the dashboard front. The those 3 lines that was just.

268 00:28:46.120 00:28:46.630 Awaish Kumar: Okay.

269 00:28:50.690 00:28:58.379 Amber Lin: Okay. Are you? Do you know all the requirements? If because, if not, we should go. Ask Cutter.

270 00:29:00.480 00:29:07.790 Awaish Kumar: Yeah. Like, as I mentioned the participant part, I’m investigating the with the current information that

271 00:29:07.950 00:29:16.330 Awaish Kumar: they spent was like more than 2,000. And we are. We are not reflecting exactly what they expect.

272 00:29:19.150 00:29:22.300 Awaish Kumar: Yeah. And the the 1st part of this description is

273 00:29:22.940 00:29:27.979 Awaish Kumar: is has has to be done in a dashboard. So it should be a separate ticket for any.

274 00:29:29.880 00:29:41.019 Amber Lin: Oh, okay, so there’s ticket one wish move.

275 00:29:43.590 00:29:47.070 Amber Lin: Is this the dashboard ticket? I thought they or is it.

276 00:29:47.070 00:29:54.629 Awaish Kumar: All this description, these 3 lines we are moving from until all the days.

277 00:29:54.630 00:29:56.100 Amber Lin: The tableau, update.

278 00:29:56.680 00:29:57.210 Awaish Kumar: Yes.

279 00:29:57.550 00:30:00.489 Amber Lin: Okay, and was you able to do that.

280 00:30:01.190 00:30:13.670 Annie Yu: I mean, I I can. But we have to get the numbers right and actually have something in parallel already. But we have to have that numbers right, I guess, or.

281 00:30:13.670 00:30:14.560 Amber Lin: Do we?

282 00:30:15.570 00:30:19.709 Amber Lin: Isn’t it synced if we move it, and then we simultaneously fix the numbers.

283 00:30:19.710 00:30:25.760 Annie Yu: Yeah, yeah, I guess. Yeah. But then the numbers for met kids and

284 00:30:27.488 00:30:29.879 Annie Yu: Hrt will probably still be wrong.

285 00:30:29.880 00:30:33.702 Amber Lin: Okay, so let’s do that first, st and then

286 00:30:34.180 00:30:35.539 Annie Yu: Have the ticket for that.

287 00:30:36.470 00:30:38.090 Amber Lin: Wait. I thought you.

288 00:30:38.280 00:30:39.460 Annie Yu: I think this.

289 00:30:39.850 00:30:42.939 Annie Yu: I think it you. This is a different one.

290 00:30:43.980 00:30:46.540 Amber Lin: Wait, what which one.

291 00:30:46.540 00:30:50.589 Annie Yu: Initially you assigned this 5, 38 to me. But then

292 00:30:52.220 00:30:57.180 Annie Yu: I flock that this is something that will need engineering’s help.

293 00:30:57.180 00:30:57.890 Amber Lin: Yeah.

294 00:30:59.860 00:31:01.020 Amber Lin: Oh, I see.

295 00:31:06.030 00:31:06.980 Amber Lin: Okay.

296 00:31:07.960 00:31:09.709 Amber Lin: Sorry. What was your request?

297 00:31:11.030 00:31:13.619 Annie Yu: No, it would be just great if I have a ticket, so I can.

298 00:31:13.620 00:31:21.810 Amber Lin: Oh, okay, yeah, no. Worries and tableau.

299 00:31:22.540 00:31:24.109 Amber Lin: And then

300 00:31:41.590 00:31:48.180 Amber Lin: wait. Is this, isn’t this the same thing? Wow? What?

301 00:31:55.690 00:31:58.660 Amber Lin: Okay, that’s the same. That’s the thing here, I think.

302 00:32:02.800 00:32:08.400 Amber Lin: You can have this ticket, and I will move this

303 00:32:08.810 00:32:15.180 Amber Lin: for a wage to the other one, so I’ll reassign this to you, and then

304 00:32:17.160 00:32:24.929 Amber Lin: can you update Cutter on when he can expect this by? I know you have 3 things now.

305 00:32:25.640 00:32:31.250 Annie Yu: And does that include getting the numbers right? Because if it.

306 00:32:31.250 00:32:34.230 Amber Lin: Oh, no, that’s not your that’s not your task.

307 00:32:34.230 00:32:34.920 Annie Yu: Okay.

308 00:32:34.920 00:32:37.669 Amber Lin: Yeah, I’ll move that here.

309 00:33:16.310 00:33:19.950 Annie Yu: Is it just me or Amber’s frozen.

310 00:33:23.430 00:33:24.409 Awaish Kumar: I can hear you.

311 00:33:25.590 00:33:27.300 Annie Yu: Can you see Amber’s screen.

312 00:33:29.480 00:33:30.409 Awaish Kumar: Yeah. Amber’s friend.

313 00:33:30.410 00:33:30.805 Annie Yu: Okay.

314 00:33:42.030 00:33:53.300 Robert Tseng: Okay, that’s it. I’m I’m gonna move to a different call. Yeah, forecast and tagging and tracking. I’ll just be making a lot of noise about those things. Alright, thanks everyone. Bye.